Automatic detection of blocked field-of-view in camera systems

ABSTRACT

Methods and apparatus for detecting a blockage in the field-of-view of a camera in an image capture system by monitoring changes in the quality of images captured by the camera. As an image is acquired by the camera, intensity values for pixels in the acquired image are determined and stored in a data structure in memory of the camera. Image statistics are calculated based in part on the intensity values for pixels in the currently acquired image and at least some previous images acquired by the camera. If the image statistics satisfy at least one predetermined alert criterion, an alert is triggered. In response to triggering an alert, an alert sensor included as part of the camera is activated to indicate to a user of the image capture system that a possible blockage in the field-of-view of the camera has been detected.

TECHNICAL FIELD

The invention relates generally to the assessment of image quality, andmore specifically to the automatic detection of a blocked field-of-viewin linescan camera systems.

BACKGROUND

With repetitive use, the lens of a camera may become dirty, resulting ina degraded image quality for images captured with the camera. Forexample, linescan camera systems capture images of objects as they passin front of a camera capture window. As objects continue to pass thecamera, obstructions and debris may collect on the camera capture windowleading to degraded quality images. The resultant degradation to imagequality may adversely impact the performance of a system in which thecamera is integrated.

A conventional method of detecting a blocked field-of-view of a camerain an imaging system includes waiting until performance of the systemdrops below a predetermined threshold. When the performance drops belowthe threshold, a user must manually investigate why the systemperformance has decreased. For example, the user decides whether or notthe performance decrease is due related to a problem with the camera orwith another part of the system. When examining the camera, the user maydetermine that the capture window of the camera is obscured by dirt ordebris and suitable maintenance (e.g., removal of the dirt or debris) isperformed to restore the system to a proper operating condition.

SUMMARY

An embodiment of the invention is directed to a method of detecting achange in a quality of images captured by a linescan camera. The methodcomprises acts of: (A) storing, in at least one first data structure,first intensity values determined for pixels in a So first image of atleast one object acquired by the linescan camera; (B) calculating atleast one first statistic based at least in part on at least some of thefirst intensity values stored in the at least one first data structure;(C) calculating at least one second statistic based at least in part onthe at least one first statistic and at least one third statisticpreviously stored on the linescan camera; and (D) triggering an alertwhen the at least one second statistic satisfies at least onepredetermined alert criterion.

Another embodiment of the invention is directed to a computer readablemedium encoded with a series of instructions that when executed on acomputer, perform a method. The method comprises storing, in at leastone data structure, first intensity values determined for pixels in afirst image of at least one object acquired by a linescan camera;calculating at least one first statistic based at least in part on atleast some of the first intensity values stored in the at least one datastructure; calculating at least one second statistic based at least inpart on the at least one first statistic and at least one thirdstatistic previously stored on the linescan camera; and triggering analert upon determining that the at least one second statistic satisfiesat least one predetermined alert criterion.

Another embodiment of the invention is directed to an image capturesystem including at least one camera. The at least one camera comprisesan image capture module for acquiring at least one image of at least oneobject; at least one storage medium for storing at least one computerprogram and at least one data structure; an alert sensor for receivingan alert message and displaying an alert; and a processor for executinga series of instructions specified in the at least one computer programto perform a method. The method comprises storing, in the at least onedata structure, first intensity values determined for pixels in a firstimage acquired by the image capture module; calculating at least onefirst statistic based at least in part on at least some of the firstintensity values stored in the at least one data structure; calculatingat least one second statistic based at least in part on the at least onefirst statistic and at least one third statistic previously stored onthe at least one storage medium; and transmitting an alert message fromthe processor to the alert sensor when the at least one second statisticsatisfies at least one predetermined alert criterion.

It should be appreciated that all combinations of the foregoing conceptsand additional concepts discussed in greater detail below (provided suchconcepts are not mutually inconsistent) are contemplated as being partof the inventive subject matter disclosed herein. In particular, allcombinations of claimed subject matter appearing at the end of thisdisclosure are contemplated as being part of the inventive subjectmatter disclosed herein.

BRIEF DESCRIPTION OF DRAWINGS

The accompanying drawings are not intended to be drawn to scale. In thedrawings, each identical or nearly identical component that isillustrated in various figures is represented by a like referencecharacter. For purposes of clarity, not every component may be labeledin every drawing. In the drawings:

FIG. 1 is an image capture system for use with some embodiments of theinvention;

FIG. 2 illustrates an exemplary object that may be imaged by an imagecapture system in accordance with some embodiments of the invention;

FIG. 3 is flow chart of a process for image quality detection accordingto some embodiments of the invention;

FIG. 4 is a flow diagram of a process for determining an image qualityfor an image captured by a linescan camera according to some embodimentsof the invention;

FIG. 5 illustrates areas of an exemplary object that may be imaged by animage capture system in accordance with some embodiments of theinvention; and

FIG. 6 illustrates an extended portion of an image of an object that maybe used to detect a false positive alert in accordance with someembodiments of the invention.

DETAILED DESCRIPTION

The present disclosure generally relates to inventive methods andapparatus for assessing the quality of an image captured by a camera todetermine if the field-of-view of the camera is obscured by dirt ordebris. Applicants have recognized and appreciated that conventionalmethods of identifying a blocked field-of-view of a camera in an imagecapture system may be improved by incorporating an automatic analysisand alert system into the image capture system. In contrast toconventional approaches where a user must manually inspect the imagecapture system to determine a cause of a performance decrease in thesystem, automated image quality detection methods and apparatus,according to embodiments of the invention, monitor the quality of imagesacquired by the image capture system to detect a potential decrease insystem performance prior to the performance of the system actuallydecreasing.

FIG. 1 illustrates an exemplary image capture system 100 for use withsome embodiments of the invention. In one embodiment, the image capturesystem 100 may be an inspection system comprising a camera 110 and aconveyor or moving stage 130. The camera 110 may be linescan camera, anarea scan camera, or any other suitable type of camera for use withimage capture system 100. The camera 110 comprises an image capturemodule 112, a processor 114 connected to the image capture module 112,and one or more storage devices such as memory 116. In some embodiments,the camera 110 comprises firmware 120 which contains one or morecomputer programs as discussed below.

In embodiments in which a linescan camera is contemplated, the imagecapture module 112 may comprise a lens, a light source, a capturewindow, and a row of photodetectors for acquiring a line image of anobject 132. The object 132 may be placed on a conveyor 130 which movesto pass the object 132 through the field-of-view 134 of the camera 110.The image capture system 100 may additionally comprise a user interface140 in which a user of the image capture system 100 may interact toadjust one or more user-configurable aspects (e.g., alert criteria asdiscussed below) of the image capture system 100. In some embodiments,the user interface 140 may include a display and one or more input keysfor entering information related to the one or more user-configurableaspects. Although embodiments of the invention described below comprisea linescan camera, it should be appreciated that camera 110 mayalternatively be an area scan camera, as embodiments of the inventionare not limited in this respect. Furthermore, a camera in accordancewith embodiments of the invention may be a grayscale camera or a colorcamera, as embodiments of the invention are not limited to any format ofcamera.

Linescan cameras are often used in applications in which it is desirableto capture a large amount of data in a short period of time. One suchapplication is the processing of mail by a mail sorting machine. In mailsorting, the object 132 may be a piece of mail as shown in FIG. 2. Thepiece of mail may comprise one or more areas which contain informationto identify the mail piece. For example, the mail piece may include astamp area 210, an address area 220, and a delivery bar code 230. Themail piece may additionally comprise one or more other graphical areassuch as designs, logos, etc. In conventional mail processing machines,the piece of mail may be placed on the conveyor 130 and the mail may beimaged as it passes through the field of view 134 of the camera 110. Thepiece of mail may be imaged to read, for example, the delivery bar code230 imprinted on the piece of mail. In some aspects, the delivery barcode 230 identifies the delivery location of the piece of mail, so thatthe mail processing machine sorts the mail based on the destination ofeach mail piece.

The one or more storage devices in camera 110 may be implemented in anyway, as embodiments of the invention are not limited in this respect.For example, memory 116 may be implemented as a solid state drive (e.g.,incorporating random access memory (RAM)), a flash memory, a hard diskdrive, or any other type of storage device. Any or all of the storagedevices in camera 110 may comprise one or more computer programs whichinclude instructions that when executed by the processor 114, mayanalyze at least a portion of the image(s) collected by the imagecapture module 112. For example, in a linescan camera, firmware 120 maybe configured to process line images as they are acquired by the imagecapture module 112. Alternatively, images or portions of images acquiredby the image capture module 112 may be processed by one or more softwareprograms stored on the memory 116 and executed on the processor 114. Itshould be appreciated that computer programs stored in firmware 120 oras software programs in the memory 116 may be implemented in any wayusing any suitable programming language, and aspects of embodiments ofthe invention are not limited in this respect.

The camera 110 further comprises an alert sensor 122 which indicates toa user of the image capture system 100 that the quality of imagescaptured by the camera 110 is degraded and accordingly, that the camera110 requires maintenance to improve the image quality. The alert sensor122 may be implemented as a light-emitting diode (LED) or other suchindicator on the camera 110 to clearly identify to the user that adegraded image quality has been detected. Alternatively, the alertsensor 122 may be incorporated as a portion of the user interface 140presented to a user of the image capture system 100, or the alert sensor122 may be implemented in any other suitable way. In some aspects, afterat least a portion of an image has been captured and analyzed, one ormore signals may be sent from the processor 114 to the alert sensor 122to change the state of the sensor if the quality of the captured imageis determined to be degraded.

FIG. 3 illustrates a exemplary process for the operation of imagecapture system 100 according to some embodiments of the invention. Asdescribed above, objects 132 such as pieces of mail may be transportedthrough a field-of-view 134 of the camera 110 to allow for imaging ofthe object. In act 310, at least a portion of the object is imaged bythe camera intensity values for pixels in the acquired image are storedin at least one of the storage devices in the camera. In embodimentswhere the camera 110 is a linescan camera, the captured image may be aline image which may be stored in memory 116 or firmware 120. Processingof line images according to various embodiments is discussed below withreference to FIG. 4.

After capturing at least a portion of an image of an object in act 310,processor 114 may execute a computer program comprising a series ofinstructions in act 320 to calculate one or more image statistics (e.g.average and variance of intensity values) from the acquired image. Itshould be appreciated that the computer program used to calculate theimage statistics may be implemented as software, firmware, or somecombination. After calculating at least some image statistics in act320, the processor 114 may execute an alert algorithm in act 330 todetermine if the image quality of the acquired image is significantlydegraded relative to a predetermined alert criterion. Examples ofsuitable alert algorithms for use with some embodiments of the inventionare described in detail below. As with the computer program(s) whichcalculate the image statistics in act 320, computer program(s) fordetermining in act 330 if alert criteria are satisfied may beimplemented in software, firmware, or some combination, as embodimentsof the invention are not limited in this respect.

The result of executing an alert algorithm in act 330 leads to adetermination in act 340 as to whether or not an alert criterion (orcriteria) has been satisfied. If the result of the alert algorithmindicates that the alert criterion has not been satisfied, then thestatistics calculated in act 320 are recorded in act 350, and a newimage may be acquired by the camera. The statistics may be stored in anysuitable manner in one or more of the storage devices in the camera, asembodiments of the invention are not limited in this respect. Forexample, the statistics calculated for the current image and one or moreprevious images may be stored in a data structure in firmware 120 ormemory 116, such that the stored statistical values for the images arereadily accessible to the processor 114 during subsequent iterations ofthe process illustrated in FIG. 3.

If it is determined in act 340 that the quality of the image acquired bythe camera is degraded (i.e., the alert criteria has been reached), andalert is triggered. Then, in act 360, it is determined if the triggeredalert is a false positive alert or a duplicate alert (e.g., from apreviously acquired image). Applicants have recognized and appreciatedthat one of the challenges of detecting a blocked field-of-view in animage capture system is to minimize and/or eliminate duplicate and falsepositive alerts. Accordingly, in some embodiments, a history of theregion of the image that triggered an alert may be stored and used as abasis for determining if the current alert is a duplicate. In otherembodiments, known factors that cause false positive alerts are takeninto consideration when determining if, in fact the alert triggered bythe current image is a false positive alert. For example, applicantshave identified that illumination degrades at the edges of an image.Thus, in some embodiments, the portions of an image close to theperiphery of the object (e.g., within 10 pixels of the edge of theimage) are not considered in calculating the statistics in act 320.Additionally, in some embodiments, objects may be profiled such thatcertain areas of the object known to be prone to triggering falsepositive alerts, and which are not necessary for proper identificationof the object, may be ignored in the statistical calculations. Othermethods of reducing the number of false positive alerts are alsocontemplated and are described in more detail below. It should beappreciated that any or all of the algorithms or methods for determiningif the current alert is a duplicate or false positive alert may beimplemented in any suitable way in software, hardware, and/or firmware,as embodiments of the invention are not limited in this respect.

In response to executing false positive and duplicate detectionalgorithms or methods in act 360, it is determined in act 370 if thecurrent alert is a duplicate or a false positive alert. If a duplicateor false positive alert is detected, the image statistics for thecurrently acquired image are recorded in act 350, and a new image may beacquired by the camera. As described above, the image statistics may bestored in any way, as embodiments of the invention are not limited inthis respect. If it is determined in act 370 that the alert is genuine(i.e., not a duplicate or a false positive), then an alert sensor isactivated in act 380 to alert the user of the blocked field-of-view ofthe camera in the image capture system. As described above, the imagecapture system 100 may include an alert sensor 122 to which one or moresignals generated by the processor 114 may be sent upon satisfaction andvalidation of the alert criteria. The alert may be transmitted to theuser of the image capture system 100 in any suitable way, such asilluminating an LED or other light-emitting alert sensor 122 located onthe camera 110 or some other portion of the image capture system 100, orby transmitting a message from the processor 114 to a user interfaceintegrated as part of the image capture system 100. For example, in someembodiments, a pre-determined message may be stored in firmware orsoftware on a storage device in the camera, and upon validation of analert in act 360, the message may be transmitted to a user to indicatethat a blocked field-of-view of the camera exists. The alert message maybe transmitted in any suitable manner, such as via a network connectionor otherwise, as embodiments of the invention are not limited in thisrespect. In addition to transmitting the alert to a user in act 380, theimage statistics may be recorded in act 350 as described above, andadditional images may be subsequently acquired and analyzed by the imagecapture system 100.

FIG. 4 illustrates an exemplary process for analyzing images capturedfrom a linescan camera according to some embodiments of the presentinvention. FIG. 5 depicts an example of an object 132 (e.g., a piece ofmail) that may be imaged using the process illustrated in FIG. 4 anddescribed in detail below. In act 410, a linescan camera captures a lineimage 510 (see FIG. 5). A line of photodectectors in a linescan camerais oriented so as to capture a line image 510 that is one pixel wide anda plurality of pixels high. For example, in an exemplary mail scanningsystem, a linescan camera may acquire line images that are 1×1600pixels, may capture 256 line images per inch of the object, and mayacquire line images at a rate of 160 inches per second. After acquiringa line image 510 in act 410, the intensity values for each of the pixelsin the line image may be determined in act 420. For example, each pixelin the line image 510 may be assigned a value ranging between 0-255(e.g., with 0 indicating black, 255 indicating white, and values between0 and 255 indicating various shades of gray) using an intensity mappingalgorithm stored in firmware 120 or in some other storage device ofcamera 110. Alternatively, in embodiments comprising a color camera, thevalue assigned to each pixel in the line image 510 may represent a colorcharacteristic (e.g., hue, saturation or value or HSV) associated withthe pixel. Although HSV is one color model that may be used withembodiments of the invention that include a color camera, it should beappreciated that any other color model may also be used, as embodimentsof the invention are not limited in this respect.

In act 430, the intensity values calculated in act 420 may be stored ina data structure in firmware 120 (or alternatively, in some otherstorage device). In some embodiments, the data structure may comprise anN×1600 array in which intensity values for each of the line images arestored. The pixels at the same height in each line image 510 form a“row” 520 of pixels (see FIG. 5) across the image (i.e., across all lineimages at the same height). In some embodiments, as each of the lineimages 510 are acquired, firmware 120 may calculate statistics for eachrow of pixels in the image. For example, firmware 120 may be configuredto calculate an average intensity value for pixels in a row and avariance of intensity values for pixels in a row. The average intensityvalue and variance of intensity value for pixels in each row of the datastructure may be stored in firmware 120 or a storage device (e.g.,memory 116) in the camera 110. To reduce the amount of data that isstored and used for further calculations, in some embodiments, theaverages and variances of intensity values from multiple rows 520 may beaveraged. For example, in one embodiment, the averages and variances foreach consecutive group of four rows 520 is averaged and stored, althoughmore or fewer (including zero) number of rows may be averaged together,as embodiments of the invention are not limited in this respect.Averaging intensity values for a row 520 may be accomplished by addingthe intensity values for pixels in the row and then dividing by thenumber of acquired pixels in the row (i.e., the number of acquired lineimages). The average intensity value for a row is an indication of thebrightness of the row. For example, an average value of 0 indicates thatall of the pixels in the row are black, and an average value if 255indicates that all of the pixels in the row are white. In general,images tend to have pixel values in the range of 20-200 indicatingvarying degrees of gray (depending on desired calibration and otherfactors). Accordingly, the average intensity value for a row istypically in a similar range (i.e., 20-200).

Applicants have recognized and appreciated that pixels in an area of theimage where obstructing objects such as dirt, debris, ink, etc. arepresent in the field-of-view 134 of the camera 110 will haveartificially lower intensity values (i.e., it will appear that thepixels are darker). Thus, rows in areas of the image that include suchobstructions may have a lower average intensity value compared to rowsin areas of the image that do not contain obstructions. Accordingly,some embodiments of the invention are directed to methods and apparatusfor detecting rows which have an abnormally low average intensity valueas an indication that a blockage in the field-of-view 134 of the camera110 is present.

In addition to calculating an average intensity value for each row, someembodiments of the invention may additionally calculate the variance ofintensity values in a row (or consecutive groups of rows as discussedabove for averaging). The variance of intensity values for pixels in arow indicates how much contrast the row contains (e.g., an image withhigh contrast will have a high variance), and contrast is a factor whichcontributes significantly to effective recognition processing andperformance of an image capture system. The variance of intensity valuesfor a row may be calculated using mean of the squares and squares of themean calculations in firmware (or software).

After processing and storing the values for one line image 510 in act430, it may be determined in act 440 if the entire image of the object132 has been captured by the image capture system 100. If the entireimage has not been captured, then more line images 510 are acquired,processed, and stored, until it is determined in act 440 that the entireimage of the object 132 has been captured. After it has been determinedthat the entire image has been acquired in act 440, the averages andvariances calculated and stored for the current image are combined inact 450 with averages and variances calculated for previously capturedimages to determine if there has been a significant degradation in theimage quality (e.g., in one or more areas of the image).

In one embodiment, computer programs stored in firmware 120 maycalculate a new array of averages and variances Y according to thefollowing formula:Y=X*δ+X ₁(1−δ),where X is a prior array of averages and variances (e.g., history), X₁is the array of averages and variances for the currently captured image,and δ is a weighting factor. Using this formula, Y then becomes X forthe next iteration (i.e., the current array is factored into the priorarray when the next image is captured). The value δ may be a decimalvalue between 0 and 1, which is user-configurable and determines theweighting given to previously captured images as compared to thecurrently acquired image. For example, if δ=0.9, then all previouslycaptured images are given 90% weight to influence when an alert shouldbe triggered.

Applicants have recognized that the first captured image will not haveany values for previously captured images. Thus, the prior array X maybe initialized using suitable values, for example, 240 for average and1000 for variance, since these values indicate an image that has a lightintensity with high contrast. It should be appreciated that differentinitialization values may alternatively be used, as embodiments of theinvention are not limited in this respect. After the average andvariance values for the currently acquired image are combined withstatistics calculated for previously acquired images in act 450,processing may proceed to act 340 in FIG. 3 to determine if any alertcriteria have been satisfied.

Although the aforementioned calculations have been described as beingcomputed in firmware, some or all of the image analysis calculations mayalternatively be implemented in software, and aspects of embodiments ofthe invention are not limited in this respect. It should also beappreciated that statistics other than, or in addition to, average andvariance of intensity values in an image may also be used to detect adegraded image quality, as embodiments of the invention are not limitedin this respect. Furthermore, whereas the image analysis calculations(e.g., average and variance) above are computed for rows of an image, itshould be appreciated that similar calculations may also be performedfor the columns of an image (e.g., if the line images of the object werecaptured in a horizontal plane rather than in a vertical plane).

Although the entire field of view may be considered in image analysiscalculations, applicants have recognized and appreciated that someobjects vary in their height (e.g., envelopes of different sizes). Thus,in some embodiments, a detected height (i.e., a cropped height) may beobtained, and the rows above the cropped height (i.e., rows 530 in FIG.5) may not be used in that iteration of the image analysis calculations.The detected height may be user-configurable, and may be set at, forexample, the height of a standard size greeting card envelope, althoughother detected heights are also possible.

In some embodiments, thresholds at which alerts are triggered may beuser configurable (e.g., via user interface 140), and the alert criteriamay utilize the averages only, the variances only, or a combination ofboth measures. Additionally, a user may set multiple alert criteria,such that more than one set of circumstances may trigger an alert to besent to the user. For instance, the user may request an alert when theaverage intensity values for 10 consecutive rows in an image fall below80 (i.e., the detected image is getting too dark), and an additionalalert when the average intensity value for 10 consecutive rows fallsbelow 100 and the variance for the same 10 consecutive rows falls below90 (i.e., image contrast is also deteriorating). It should beappreciated that the optimal settings may be application-specific andmay be determined using an iterative process or other methods, ascreating thresholds that are too stringent may result in too few alertsbeing triggered, whereas thresholds that are too relaxed may result intoo many false positive alerts being triggered. One way to mitigate thechallenge in selecting appropriate alert criteria, yet still allowingfor relatively relaxed thresholds may be to control the number of falsepositive alerts by using additional information acquired by the imagecapture system.

In addition to the aforementioned methods of detecting false positivealerts (e.g., ignoring certain areas of the object not used for objectrecognition, etc.), other methods may also be used to inform thedetection process. For example, in some embodiments, images may becaptured without any object present in the camera's field of view.Applicants have recognized that this approach may be particularlybeneficial for detecting trapped paper flecks (or other such smallobjects) that may obscure the capture window of the camera and mayexhibit a blockage that has a predominantly reverse contrast (i.e.,light on a dark background).

As described above with reference to FIG. 3, and as illustrated in FIG.6, an object 132 (e.g., apiece of mail) may comprise multiple areasincluding a stamp area 210, and address area 220, and a delivery barcode230. However, applicants have recognized and appreciated that someobjects may also include designs or markings such as stripe 620, whichmay trigger a false positive alert (e.g., because it is dark and has alow contrast). To identify false positive alerts due at least in part toone or more markings on the object (rather than due to a blocked fieldof view of the camera), in some embodiments of the invention, an imagecapture system may acquire an image that is larger than the actual imageof the object. In this method, images are captured of areas (i.e.,“evaluation regions”) between objects on the conveyor 130 and theseimages are compared to images acquired for the preceding object. One ormore inconsistencies detected between an evaluation region 610 and theactual image of the object 132 provide evidence of a false positivealert. In the example of FIG. 6, an object 132 contains a stripe 620 andan evaluation region 610 adjacent to the object 132 does not contain thestripe. A comparison of images of the evaluation region 610 and theobject 132 allows for the detection of inconsistencies. For example, theabsence of the stripe 620 in the evaluation region image signifies thatan alert triggered by an image of the object 132 may have beenerroneously caused by markings on the object 132 (i.e., stripe 620) andnot by a blocked field-of-view of the camera. Image comparisons may beperformed in any suitable way, as embodiments of the invention are notlimited in this respect. For example, in some embodiments, theevaluation region 610 may be analyzed in a similar manner as the imageof object 132 by calculating averages and variances of the intensityvalues of the evaluation region image, and the calculated averages andvariances for the evaluation region image and the object image may becompared.

In some embodiments, one or more trigger points (e.g., regions of animage) for an alert generated based on the image of object 132 may becompared with an alert trigger point (if any) generated by analysis ofthe image of the evaluation region 610. A match of the two alert triggerpoints may signify the existence of an obstruction in the field-of viewof the camera. Otherwise, the alert may be considered as a falsepositive alert due to a marking on the object 132, and the alert isignored. It should be appreciated that stripe 620 shown on the object132 in FIG. 6 is only one example of a type of marking on an object thatmay trigger a false positive alert, and detection of other types ofmarkings and designs for determining false positive alerts are alsocontemplated by embodiments of the invention.

In some embodiments, when an alert is sent to a user, at least someinformation associated with the alert may be stored in a logfile on theimage capture system (or elsewhere). By recording the occurrences ofgenerated alerts, users may be able to identify certain image capturesystems which are more prone to blockages of the field-of-view of acamera in the image capture systems, and additional maintenance may berequired on such image capture systems to prevent the reoccurrence of atleast some of the blockages.

Having thus described several aspects of at least one embodiment of thisinvention, it is to be appreciated that various alterations,modifications, and improvements will readily occur to those skilled inthe art.

Such alterations, modifications, and improvements are intended to bepart of this disclosure, and are intended to be within the spirit andscope of the invention. Accordingly, the foregoing description anddrawings are by way of example only.

The above-described embodiments of the present invention can beimplemented in any of numerous ways. For example, the embodiments may beimplemented using hardware, software, firmware, or a combination thereofWhen implemented in firmware or software, the instructions containedtherein can be executed on any suitable processor or collection ofprocessors, whether provided in a single computer or distributed amongmultiple computers.

Further, it should be appreciated that a computer may be embodied in anyof a number of forms, such as a rack-mounted computer, a desktopcomputer, a laptop computer, or a tablet computer. Additionally, acomputer may be embedded in a device not generally regarded as acomputer but with suitable processing capabilities, including a PersonalDigital Assistant (PDA), a smart phone or any other suitable portable orfixed electronic device.

Also, a computer may have one or more input and output devices. Thesedevices can be used, among other things, to present a user interface.Examples of output devices that can be used to provide a user interfaceinclude printers or display screens for visual presentation of outputand speakers or other sound generating devices for audible presentationof output. Examples of input devices that can be used for a userinterface include keyboards, and pointing devices, such as mice, touchpads, and digitizing tablets. As another example, a computer may receiveinput information through speech recognition or in other audible format.

Such computers may be interconnected by one or more networks in anysuitable form, including as a local area network or a wide area network,such as an enterprise network or the Internet. Such networks may bebased on any suitable technology and may operate according to anysuitable protocol and may include wireless networks, wired networks orfiber optic networks.

Also, the various methods or processes outlined herein may be coded assoftware that is executable on one or more processors that employ anyone of a variety of operating systems or platforms. Additionally, suchsoftware may be written using any of a number of suitable programminglanguages and/or programming or scripting tools, and also may becompiled as executable machine language code or intermediate code thatis executed on a framework or virtual machine.

In this respect, the invention may be embodied as a computer readablemedium (or multiple computer readable media) (e.g., a computer memory,one or more floppy discs, compact discs, optical discs, magnetic tapes,flash memories, circuit configurations in Field Programmable Gate Arraysor other semiconductor devices, or other tangible computer storagemedium) encoded with one or more programs that, when executed on one ormore computers or other processors, perform methods that implement thevarious embodiments of the invention discussed above. The computerreadable medium or media can be transportable, such that the program orprograms stored thereon can be loaded onto one or more differentcomputers or other processors to implement various aspects of thepresent invention as discussed above.

The terms “program” or “software” are used herein in a generic sense torefer to any type of computer code or set of computer-executableinstructions that can be employed to program a computer or otherprocessor to implement various aspects of the present invention asdiscussed above. Additionally, it should be appreciated that accordingto one aspect of this embodiment, one or more computer programs thatwhen executed perform methods of the present invention need not resideon a single computer or processor, but may be distributed in a modularfashion amongst a number of different computers or processors toimplement various aspects of the present invention.

Computer-executable instructions may be in many forms, such as programmodules, executed by one or more computers or other devices. Generally,program modules include routines, programs, objects, components, datastructures, etc. that perform particular tasks or implement particularabstract data types. Typically the functionality of the program modulesmay be combined or distributed as desired in various embodiments.

Also, data structures may be stored in computer-readable media in anysuitable form. For simplicity of illustration, data structures may beshown to have fields that are related through location in the datastructure. Such relationships may likewise be achieved by assigningstorage for the fields with locations in a computer-readable medium thatconveys relationship between the fields. However, any suitable mechanismmay be used to establish a relationship between information in fields ofa data structure, including through the use of pointers, tags or othermechanisms that establish relationship between data elements.

Various aspects of the present invention may be used alone, incombination, or in a variety of arrangements not specifically discussedin the embodiments described in the foregoing and is therefore notlimited in its application to the details and arrangement of componentsset forth in the foregoing description or illustrated in the drawings.For example, aspects described in one embodiment may be combined in anymanner with aspects described in other embodiments.

Also, the invention may be embodied as a method, of which an example hasbeen provided. The acts performed as part of the method may be orderedin any suitable way. Accordingly, embodiments may be constructed inwhich acts are performed in an order different than illustrated, whichmay include performing some acts simultaneously, even though shown assequential acts in illustrative embodiments.

Use of ordinal terms such as “first,” “second,” “third,” etc., in theclaims to modify a claim element does not by itself connote anypriority, precedence, or order of one claim element over another or thetemporal order in which acts of a method are performed, but are usedmerely as labels to distinguish one claim element having a certain namefrom another element having a same name (but for use of the ordinalterm) to distinguish the claim elements.

Also, the phraseology and terminology used herein is for the purpose ofdescription and should not be regarded as limiting. The use of“including,” “comprising,” or “having,” “containing,” “involving,” andvariations thereof herein, is meant to encompass the items listedthereafter and equivalents thereof as well as additional items.

1. A method of detecting a change in a quality of images captured by alinescan camera, the method comprising acts of: (A) storing, in at leastone first data structure, first intensity values determined for pixelsin a first image of at least one object acquired by the linescan camera;(B) calculating at least one first statistic based at least in part onat least some of the first intensity values stored in the at least onefirst data structure; (C) calculating at least one second statisticbased at least in part on the at least one first statistic and at leastone third statistic previously stored on the linescan camera; and (D)triggering an alert when the at least one second statistic satisfies atleast one predetermined alert criterion.
 2. The method of claim 1,wherein calculating the at least one second statistic comprisesmultiplying the at least one third statistic by a weighting factor. 3.The method of claim 1, wherein the at least one first statistic includesat least one of an average intensity value for at least one row ofpixels in the first image and a variance of intensity values for the atleast one row of pixels in the first image.
 4. The method of claim 1,wherein the act of triggering an alert further comprises determining ifthe alert is a duplicate alert or a false positive alert.
 5. The methodof claim 4, wherein determining if the alert is the false positive alertcomprises acquiring a third image and comparing at least a portion ofthe third image with at least a portion of the first image, wherein thethird image does not contain the at least one object.
 6. The method ofclaim 1, wherein calculating the at least one first statistic comprisesexcluding at least some of the first intensity values.
 7. The method ofclaim 6, wherein calculating the at least one first statistic comprisesexcluding the first intensity values for pixels close to the peripheryof the first image.
 8. The method of claim 1, wherein the at least onepredetermined alert criterion includes an criterion based on an averageintensity value and a variance in intensity values.
 9. The method ofclaim 1, further comprising the act: (E) storing in at least one seconddata structure the at least one second statistic.
 10. A non-transitorycomputer readable medium encoded with a series of instructions that whenexecuted on a computer, perform a method, the method comprising:storing, in at least one data structure, first intensity valuesdetermined for pixels in a first image of at least one object acquiredby a linescan camera; calculating at least one first statistic based atleast in part on at least some of the first intensity values stored inthe at least one data structure; calculating at least one secondstatistic based at least in part on the at least one first statistic andat least one third statistic previously stored on the linescan camera;and triggering an alert upon determining that the at least one secondstatistic satisfies at least one predetermined alert criterion.
 11. Thenon-transitory computer readable medium of claim 10, wherein the atleast one data structure comprises an array having a plurality of rowsand a plurality of columns, and wherein the at least one predeterminedalert criterion includes a criterion based on at least one of an averageintensity value in at least two adjacent rows of the plurality of rowsor at least two adjacent columns of the plurality of columns and avariance in intensity values in at least two adjacent rows of theplurality of rows or at least two adjacent columns of the plurality ofcolumns.
 12. The non-transitory computer readable medium of claim 10,wherein calculating the at least one first statistic comprises excludingthe first intensity values for pixels close to the periphery of thefirst image.
 13. The non-transitory computer readable medium of claim10, wherein the alert is deleted upon determining that the alert is aduplicate alert or a false positive alert.
 14. The non-transitorycomputer readable medium of claim 10, wherein at least a portion of theat least one first statistic is calculated prior to acquisition of theentire first image.
 15. An image capture system including at least onecamera, the at least one camera comprising: an image capture module foracquiring at least one image of at least one object; at least onestorage medium for storing at least one data structure; an alert sensorfor receiving an alert message and displaying an alert; and at least oneprocessor programmed to: store, in the at least one data structure,first intensity values determined for pixels in a first image acquiredby the image capture module; calculate at least one first statisticbased at least in part on at least some of the first intensity valuesstored in the at least one data structure; calculate at least one secondstatistic based at least in part on the at least one first statistic andat least one third statistic previously stored on the at least onestorage medium; and transmit the alert message to the alert sensor inresponse to determining that the at least one second statistic satisfiesat least one predetermined alert criterion.
 16. The image capture systemof claim 15, wherein at least one computer program is implemented infirmware and at least a portion of the at least one first statistic iscalculated prior to acquiring the entire first image.
 17. The imagecapture system of claim 15, further comprising a conveyor fortransporting the at least one object past a field-of-view of the imagecapture module.
 18. The image capture system of claim 15, wherein theimage capture system is a mail sorting apparatus and the at least oneobject includes a piece of mail.
 19. The image capture system of claim15, wherein the alert sensor is a sensor which emits light in responseto receiving the alert message.
 20. The image capture system of claim15, wherein the alert sensor is a user interface comprising a display,and wherein the alert message is presented on the display of the userinterface in response to receiving the alert message.